(...) dass wir unsere eigenen Artgenossen statistisch nachweisbar nicht mehr zuverlässig erkennen. Herausgekommen war unter dem Strich also weniger, dass Maschinen wie Menschen kommunizieren können, sondern dass Menschen mittlerweile so sehr wie Maschinen ticken, dass sie den Unterschied nicht mehr beurteilen können
images that correspond so well to the style of the films suggests that the AI model has been trained with the films from Studio Ghibli. The question now arises as to whether OpenAI was allowed to use the films for training
Mit dem AI Pin wollte Humane unsere Abhängigkeit von Bildschirmen beenden und das Smartphone ablösen. Das ist gescheitert, die Geräte werden nun Elektroschrott
Alex: Developed AI drone swarms for disaster relief at 18. Graduated with top honours from Imperial. His job? Tweaking a single button's ergonomics on home appliances.
These aren't outliers. They're a generation of engineering prodigies whose talents are being squandered.
This isn't just wage disparity. It's misallocation of human capital on a national scale.
So the AI boom of the last 12 years was made possible by three visionaries:
One was Geoffrey Hinton, a University of Toronto computer scientist who spent decades promoting neural networks despite near-universal skepticism.
The second was Jensen Huang, the CEO of Nvidia, who recognized early that GPUs could be useful for more than just graphics.
The third was Fei-Fei Li. She created an image dataset that seemed ludicrously large to most of her colleagues. But it turned out to be essential for demonstrating the potential of neural networks trained on GPUs
5 types of AI personalities in the workplace:
“The Maximalist” who regularly uses AI on their jobs; “The Underground" who covertly uses AI; “The Rebel,” who abhors AI; “The Superfan” who is excited about AI but still hasn't used it; and “The Observer" who is taking a wait-and-see approach